Research map / Vision-language and multimodal / Human and embodied modeling
Diverse Beam Search for Improved Description of Complex Scenes
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| replace beam search with diverse beam search | captioning LSTM · COCO | Oracle SPICE@20: 27.34 -> 28.09 | Helped |
| replace beam search with diverse beam search | captioning LSTM · COCO | distinct 4-grams: 5.67 -> 13.44 | Helped |
| replace BS with DBS on harder images | captioning LSTM · COCO by image complexity | Oracle SPICE@20 gain: 0.67 / 0.91 / 1.13 | Helped |
| replace BS with DBS | captioning LSTM · PASCAL-50S | Oracle SPICE@20: 8.74 -> 9.293 | Helped |
| replace BS with DBS | VQG model · VQG | SPICE: 15.17 -> 16.49 | Helped |
| replace BS with DBS | GRU NMT · En-Fr newstest-2013 | BLEU-4: 13.52 -> 13.69 | Helped |
| DBS vs Li et al. (2015) MMI decoding | GRU NMT · En-Fr newstest-2013 | Oracle BLEU-4@20: 18.86 -> 18.77 | Hurt |
| replace BS with DBS | captioning LSTM · COCO human study | human preference: 60% | Helped |
| use hamming diversity instead of n-gram, cumulative or embedding diversity (ablation) | DBS · PASCAL-50S | Oracle CIDEr@k | Helped |
| set groups G=B (max exploration) vs G=1 (ablation) | DBS · validation | oracle accuracy | Helped |
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